| 11. |
- Ade, Florian, et al.
(författare)
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When can we trust population thresholds in regression discontinuity designs? : a comment on Egger and Koethenbuerger
- 2010
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- A recent literature has used variation just around deterministic legislative population thresholds to identify the causal effects of institutional changes. This paper reviews the use of regression discontinuity designs using such population thresholds. Our concern involves three arguments: (1) simultaneous exogenous (co-)treatment, (2) simultaneous endogenous choices and (3) manipulation and precise control over population measures. Revisiting the study by Egger and Koethenbuerger (2010), who analyse the relationship between council size and government spending, we present new evidence that these three concerns do matter for causal analysis. Our results suggest that empirical designs using population thresholds are only to be used with utmost care and confidence in the precise institutional setting.
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| 12. |
- Ade, P. A. R., et al.
(författare)
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A Constraint on Primordial B-modes from the First Flight of the Spider Balloon-borne Telescope
- 2022
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Ingår i: Astrophysical Journal. - : American Astronomical Society. - 0004-637X .- 1538-4357. ; 927:2
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Tidskriftsartikel (refereegranskat)abstract
- We present the first linear polarization measurements from the 2015 long-duration balloon flight of SPIDER, which is an experiment that is designed to map the polarization of the cosmic microwave background (CMB) on degree angular scales. The results from these measurements include maps and angular power spectra from observations of 4.8% of the sky at 95 and 150 GHz, along with the results of internal consistency tests on these data. While the polarized CMB anisotropy from primordial density perturbations is the dominant signal in this region of sky, Galactic dust emission is also detected with high significance. Galactic synchrotron emission is found to be negligible in the SPIDER bands. We employ two independent foreground-removal techniques to explore the sensitivity of the cosmological result to the assumptions made by each. The primary method uses a dust template derived from Planck data to subtract the Galactic dust signal. A second approach, which constitutes a joint analysis of SPIDER and Planck data in the harmonic domain, assumes a modified-blackbody model for the spectral energy distribution of the dust with no constraint on its spatial morphology. Using a likelihood that jointly samples the template amplitude and r parameter space, we derive 95% upper limits on the primordial tensor-to-scalar ratio from Feldman-Cousins and Bayesian constructions, finding r < 0.11 and r < 0.19, respectively. Roughly half the uncertainty in r derives from noise associated with the template subtraction. New data at 280 GHz from SPIDER´s second flight will complement the Planck polarization maps, providing powerful measurements of the polarized Galactic dust emission.
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| 13. |
- Aghanavesi, Somayeh, et al.
(författare)
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Measuring temporal irregularity in spiral drawings of patients with Parkinson’s disease
- 2017
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Ingår i: Abstracts of the 21<sup>st</sup> International Congress of Parkinson's Disease and Movement Disorders. - : John Wiley & Sons. ; , s. s252-s252
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Konferensbidrag (populärvet., debatt m.m.)abstract
- Objective: The aim of this work is to evaluate clinimetric properties of a method for measuring Parkinson’s disease (PD) upper limb temporal irregularities during spiral drawing tasks.Background: Basal ganglia fluctuations of PD patients are associated with motor symptoms and relating them to objective sensor-based measures may facilitate the assessment of temporal irregularities, which could be difficult to be assessed visually. The present study investigated the upper limb temporal irregularity of patients at different stages of PD and medication time points.Methods: Nineteen PD patients and 22 healthy controls performed repeated spiral drawing tasks on a smartphone. Patients performed the tests before a single levodopa dose and at specific time intervals after the dose was given. Three movement disorder specialists rated the videos of patients' performance according to six items of UPDRS-III, dyskinesia (Dys), and Treatment Response Scale (TRS). A temporal irregularity score (TIS) was developed using approximate entropy (ApEn) method. Differences in mean TIS between two groups of patients and healthy subjects, and also across four subject groups: early, intermediate, advanced patients and, healthy subjects were assessed. The relative ability of TIS to detect changes from baseline (no medication) to later time points when patients were on medication was assessed. Correlations between TIS and clinical rating scales were assessed by Pearson correlation coefficients and test-retest reliability of TIS was measured by intra-class correlation coefficients (ICC).Results: The mean TIS was significantly different between healthy subjects and patients (P<0.0001). When assessing the changes in relation to treatment, clinical-based scores (TRS and Dys) had better responsiveness than TIS. However, the TIS was able to capture changes from Off to On, and the wearing off effects. Correlations between TIS and clinical scales were low indicating poor validity. Test-retest reliability correlation coefficient of the mean TIS was good (ICC=0.67).Conclusions: Our study found that TIS was able to differentiate spiral drawings drawn by patients from those drawn by healthy subjects. In addition, TIS could capture changes throughout the levodopa cycle.TIS was weakly correlated to clinical ratings indicating that TIS measures high frequency upper limb temporal irregularities that could be difficult to be detected during clinical observations.
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| 14. |
- Aghanavesi, Somayeh, 1981-, et al.
(författare)
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Objective assessment of Parkinson’s disease motor symptoms during leg agility test using motion sensors
- 2018
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Konferensbidrag (refereegranskat)abstract
- Title: Objective assessment of Parkinson’s disease motor symptoms during leg agility test using motion sensorsObjective: To develop and evaluate machine learning methods for assessment of Parkinson’s disease (PD) motor symptoms using leg agility (LA) data collected with motion sensors during a single dose experiment.Background: Nineteen advanced PD patients (Gender: 14 males and 5 females, mean age: 71.4, mean years with PD: 9.7, mean years with levodopa: 9.5) were recruited in a single center, open label, single dose clinical trial in Sweden [1].Methods: The patients performed up to 15 LA tasks while wearing motions sensors on their foot ankle. They performed tests at pre-defined time points starting from baseline, at the time they received a morning dose (150% of their levodopa equivalent morning dose), and at follow-up time points until the medication wore off. The patients were video recorded while performing the motor tasks. and three movement disorder experts rated the observed motor symptoms using 4 items from the Unified PD Rating Scale (UPDRS) motor section including UPDRS #26 (leg agility), UPDRS #27 (Arising from chair), UPDRS #29 (Gait), UPDRS #31 (Body Bradykinesia and Hypokinesia), and dyskinesia scale. In addition, they rated the overall mobility of the patients using Treatment Response Scale (TRS), ranging from -3 (very off) to 3 (very dyskinetic). Sensors data were processed and their quantitative measures were used to develop machine learning methods, which mapped them to the mean ratings of the three raters. The quality of measurements of the machine learning methods was assessed by convergence validity, test-retest reliability and sensitivity to treatment.Results: Results from the 10-fold cross validation showed good convergent validity of the machine learning methods (Support Vector Machines, SVM) with correlation coefficients of 0.81 for TRS, 0.78 for UPDRS #26, 0.69 for UPDRS #27, 0.78 for UPDRS #29, 0.83 for UPDRS #31, and 0.67 for dyskinesia scale (P<0.001). There were good correlations between scores produced by the methods during the first (baseline) and second tests with coefficients ranging from 0.58 to 0.96, indicating good test-retest reliability. The machine learning methods had lower sensitivity than mean clinical ratings (Figure. 1).Conclusions: The presented methodology was able to assess motor symptoms in PD well, comparable to movement disorder experts. The leg agility test did not reflect treatment related changes.
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| 15. |
- Akrami, Nazar, et al.
(författare)
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Prejudice: Its Personality and Social Psychology Components
- 2004
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Ingår i: The 28th International Congress of Psychology, Beijing, China.
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- This paper focuses on the personality and social psychology approaches to explaining prejudice. We examined whether prejudice (sexism) is better explained by personality (Big-Five factors, Social dominance orientation, and Right-wing authoritarianism) or social group membership (gender). Based on our previous research, alternative causal models were compared. The results showed that the best-fitting causal model to explain prejudice was the one that included the personality as well as social group membership variables. This outcome, also supported by multiple regression analyses, suggests that an integration of the personality and the social psychology approaches to explaining prejudicial beliefs would be the best option.
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| 16. |
- Aghanavesi, S., et al.
(författare)
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Motion Sensor-Based Assessment of Parkinson's Disease Motor Symptoms During Leg Agility Tests: Results From Levodopa Challenge
- 2020
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Ingår i: Ieee Journal of Biomedical and Health Informatics. - : Institute of Electrical and Electronics Engineers (IEEE). - 2168-2194 .- 2168-2208. ; 24:1, s. 111-119
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Tidskriftsartikel (refereegranskat)abstract
- Parkinsons disease (PD) is a degenerative, progressive disorder of the central nervous system that mainly affects motor control. The aim of this study was to develop data-driven methods and test their clinimetric properties to detect and quantify PD motor states using motion sensor data from leg agility tests. Nineteen PD patients were recruited in a levodopa single dose challenge study. PD patients performed leg agility tasks while wearing motion sensors on their lower extremities. Clinical evaluation of video recordings was performed by three movement disorder specialists who used four items from the motor section of the unified PD rating scale (UPDRS), the treatment response scale (TRS) and a dyskinesia score. Using the sensor data, spatiotemporal features were calculated and relevant features were selected by feature selection. Machine learning methods like support vector machines (SVM), decision trees, and linear regression, using ten-fold cross validation were trained to predict motor states of the patients. SVM showed the best convergence validity with correlation coefficients of 0.81 to TRS, 0.83 to UPDRS 31 (body bradykinesia and hypokinesia), 0.78 to SUMUPDRS (the sum of the UPDRS items: 26-leg agility, 27-arising from chair, and 29-gait), and 0.67 to dyskinesia. Additionally, the SVM-based scores had similar test-retest reliability in relation to clinical ratings. The SVM-based scores were less responsive to treatment effects than the clinical scores, particularly with regards to dyskinesia. In conclusion, the results from this study indicate that using motion sensors during leg agility tests may lead to valid and reliable objective measures of PD motor symptoms.
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| 17. |
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| 18. |
- Ilsøe, Anna, et al.
(författare)
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Fast-track Sociology? Reflections on Research During a Pandemic
- 2023
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Ingår i: Nordic Journal of Working Life Studies. - 2245-0157. ; 13:S10, s. 139-147
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Tidskriftsartikel (refereegranskat)abstract
- When the coronavirus spread globally in early 2020, many governments issued national lock downs of schools, institutions, and businesses. As the epidemic turned into a pandemic, the health crisis also became a societal crisis, and many universities and research foundations issued COVID-19 grants to study the societal implications of the crisis. In this article, we discuss sociological research during the corona crisis and ask the questions: What role did sociology play in the pandemic – and how did the pandemic affect sociology? We argue that trends of a fast-track sociology can be observed, which has implications for methods, theory, analysis, and societal impact. Fast-track sociology is often faster,more interdisciplinary and dialogue-based, disseminates more preliminary results, and has potential of more societal impact. However, it also contains challenges if it is not interlinked with more critical and slower research processes, which are core to the sociological profession.
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| 19. |
- Maltais, Aaron, et al.
(författare)
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Policy priorities for mobilizing investment in Swedish green industrial transitions
- 2022
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- In its latest assessment reports, the Intergovernmental Panel on Climate Change stresses that there is a rapidly closing window of opportunity for global action to prevent and adapt to climate change and that mitigation and adaptation is needed now. The Swedish Climate Policy Council has stated that a transition has been initiated in Sweden, and national emissions have been cut by about 35% since 1990. Still an acceleration of this transition is needed to reach the national target of net-zero emissions by 2045. Industry is responsible for about a third of Sweden’s greenhouse gas emissions, and investments in deep emissions cuts in this sector are key for reaching the national target. This involves investments in innovative technologies that enable increased efficiency in the use of materials and energy, increased circularity, and fuel and feedstock switches. For most industrial sectors several pathways are being implemented, although there remain large uncertainties and risks associated with the options they are pursuing.The implementation of new technologies will often increase both capital needs and operating costs and there might be periods of elevated working capital as investments in new technologies have to overlap old production processes while verifying new solutions. Moreover, industrial sites have long lifetimes and long investment cycles. As a result, investments in technological and production changes that bring deep emissions cuts in heavy industry risk older assets having to be written off prematurely. Details are scarce on the extent to which capital investment entails a challenge for industrial transition and if so how to handle these challenges. The aim of this report is to better understand the key challenges for investments in technological and production changes that bring deep emissions cuts in heavy industry in Sweden. We investigate this matter from the perspective of both industry actors and actors from the financial sector. Our key research questions are: • Is the size of the capital investments needed for green industrial production a significant challenge for bringing about these transitions in Sweden?• What are the most important challenges for actors’ willingness to invest in deep green industrial transitions and investors’ willingness to provide financing for those investments?• What policies do industrial and financial actors think can best support the willingness to invest in and provide financing for deep green industrial transitions in Sweden? The report focuses on Sweden and the heavy industries that account for the largest share of greenhouse gas emissions: iron and steel, cement, refining and chemicals. We also include the pulp and paper industry in this study given that it is a large industrial point source of biogenic CO2 emissions (through the combustion of bio-fuels) and has the potential to contribute to meeting the national net-zero target with so-called “negative emissions”.The study focuses on technological alternatives that can lead to radical reductions of direct emissions. This means that incremental energy efficiency measures and reduced demand, although important, are not considered. Our results are based on interviews with representatives from key industrial firms and financial firms and institutions. Our main results and recommendations: 1. Neither the scale of investments nor access to financing are significant obstacles to deep green industrial transformation. Our key finding is that neither the scale of capital investments in deep green industrial transition nor access to financing to make these investments are perceived to be significant obstacles by industry or financial actors. The scale of investments is large and for many industrial actors there are needs for direct support for early-stage development of new technologies and production processes. However, given a viable business case for green industrial products, capital requirements and access to finance do not appear to be critical obstructions once companies are prepared for commercial level deployments. Instead, our interviewees emphasized issues related to creating market demand and infrastructure and permitting processes as most important for enabling investments in deep green industrial transitions.2. Loan guarantees are an appropriate method of risk sharing for commercial-scale investments in deep green industrial transitions. According to our results, industry and financial actors find that existing direct financial support mechanisms and government credit guarantees are appropriate support and risk sharing tools. Our results do not point to any specific and new financing support mechanisms that industry and financial actors would like government to put in place. However, respondents did indicate that the scale of government support, both direct financial support and financial risk sharing, may need to be ramped up as industrial decarbonization pathways move from early stages to demonstration and commercial deployment.3. Policies for improving the terms of financing will not likely play a large role in mobilizing the willingness to invest in deep green industrial transitions. Industrial and financial actors stated that securing financing for green industrial transitions will likely not be a challenge when the business case for making these investments is in place. Improving the terms of financing was not prioritized among our respondents as a key lever for improving business cases. Favourable financing terms certainly contribute, but our respondents pointed to issues of market demand, direct financial support for early development, infrastructure and permitting policies as much more important. As such, decision-makers should focus on these areas for the largest effects. Importantly, our respondents’ comparatively minor concerns regarding financing should be understood in the context of the early stage of development of deep green industrial transition. As many of the major investment decisions have yet to be made, our results may not reflect challenges that could occur at the point of commercial deployment. Moreover, it is very difficult to predict how financial markets will develop over the long timeframes over which investments in deep green industrial transitions are needed. As such it is still too early to make a judgement on the extent to which policy efforts could be needed to mobilize financing towards these transitions.4. If needs for new financing solutions become apparent over time, public authorities will likely need to take a leadership role and set in motion proposals and dialogue with relevant private actors. We did not find developed ideas among industry or financial actor respondents for new financing solutions for green industrial transitions. This reflects both the perspective that financing is not a major obstacle and the early stage of development and deployment in some sectors. Because our results did not find forward-looking strategies in this area, decision-makers can contribute to green industrial transitions by tasking public authorities with investigating potential needs, gaps and innovative financing solutions for green industry transitions for future stages of deployment when capital requirements can become very high.5. Policymakers should focus on market formation efforts. Particularly important are efforts at the European Union level to ensure that carbon price signals are high enough to create business cases for green industrial products and that efforts to prevent carbon leakage maintain fair competition. Our results show that the key policy space for mobilizing investments into green industry is in supporting market formation and demand for green industrial products. As confidence in technological solutions advances, more attention is focused on how the increased costs of green production can be transferred to end consumers. The most desired market generation policies from both industry and finance are general policies like carbon taxes combined with measures to protect the competitiveness of industries, for example a carbon border adjustment mechanism (CBAM).6. The methods for and extent of demand-generating policies should be considered sector by sector as there may be divergence on the degree to which general policies and bottom-up approaches achieve the desired pace of change in different sectors. In addition to general market formation efforts, some actors emphasized demand generation policies directed at specific sectors, motivated by the different prerequisites for transition in those sectors. For example, public procurement policies for green industrial products were put forward as important for the cement sector especially. Another example, particularly important for the refining sector, are the policies requiring the blending of biofuels into petrol and diesel, which are already being implemented.7. Both investors and policymakers should continue to push for companies to deliver transparency and target setting with respect to their scope 3 emissions. Working with value chains to create demand for green industrial products can accelerate the pace of transitions as has been proven in the case of green steel production in Sweden. Repeating this dynamic in other emissions-intensive industrial sectors is crucial. Our respondents emphasize that setting targets for emissions reduction and transparent reporting about progress towards these targets are important to stimulate transition not only of individual firms but also of whole value chains.8. Government should continue with its existing financial support mechanism, reviewing financing needs periodically, and work to ensure that Swedish industry is able to access support measures at the EU level. Although our respondents indicated that access to financing for commercial deployment (assuming good market demand indications) is good, publ
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| 20. |
- Barabash, S., et al.
(författare)
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Observations of Sounder Accelerated Electrons by Mars Express
- 2020
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Ingår i: Journal of Geophysical Research - Space Physics. - 2169-9380 .- 2169-9402. ; 125:1
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Tidskriftsartikel (refereegranskat)abstract
- The electron sensor of the Analyzer of Space Plasmas and Energetic Atoms experiment detects accelerated electrons during pulses of radio emissions from the powerful topside sounder: the Mars Advanced Radar for Subsurface and Ionosphere Sounding (MARSIS) on board the Mars Express spacecraft. Accelerated electrons are observed at energies up to 400 eV at the times when MARSIS transmits at a frequency between the local plasma frequency and its harmonics (up to 4 times the plasma frequency). When the electron density and magnetic field strength are low (similar to 10(3) cm(-3), similar to 10 nT), the accelerated electrons are almost monoenergetic electron beams. An increase in density and magnetic field (similar to 3 . 10(3) cm(-3), similar to 50 nT) leads to substantial broadening of the energy spectrum of the accelerated electrons. It is concluded that in the latter case, electrons are accelerated by the variable spacecraft potential resulting from the imbalance of the electron and ion currents to the MARSIS antenna during transmission.
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